Predictors of Acute and Chronic PTSD in Road Trauma Survivors: Insights from a 12-Month Cohort Study
Bibliographic record
Abstract
Introduction: The present study reports the prevalence of acute post-traumatic stress disorder (PTSD) symptoms (2 months post-injury) and chronic PTSD symptoms (6 and 12 months post-injury) among road trauma survivors. We also examine baseline factors as potential predictors of acute and chronic PTSD symptoms post-injury. Methods: This study followed a prospective cohort, enrolling 1480 survivors in Canada, between July 2018 and March 2020. PTSD symptoms were measured with the Post-traumatic Check-List Scale (PCL-S) at 2, 6, and 12 months post-injury. Baseline sociodemographic, psychological, medical, and injury-related factors were examined as predictors of acute and long-term PTSD symptoms using multivariable logistic regression. Results: PTSD symptoms were reported by 241 of 1074 participants (22.4%) at 2 months, 167 of 935 (17.9%) at 6 months, and 141 of 872 (16.2%) at 12 months. Female sex, Asian ethnicity, more retrospectively reported pre-injury somatic symptoms, greater pre-injury psychological distress, and being a pedestrian (vs a driver) were consistently linked to higher odds of PTSD symptoms at 2 and 6 months. At 2 months, younger age, greater pre-injury pain catastrophizing, uncertain recovery expectations, and head or spine/back injuries were additional significant predictors, while by 6 months, having neck injury remained significant. By 12 months, chronic PTSD symptoms was associated with greater pre-injury pain catastrophizing, lower pre-injury health-related quality of life, and spine/back injury. Injury pain remained a predictor across all follow-ups. Conclusion: PTSD symptom prevalence among survivors decreased between 2 and 6 months post-injury, but recovery rate slowed thereafter, with reduction between 6 and 12 months being much smaller than the earlier decrease. Furthermore, as some significant factors are modifiable, early interventions-such as effective pain management, psychological support, and coping strategy training-may help mitigate PTSD symptoms. Brief screening for psychological distress and pain catastrophizing could further support timely identification and referral of high-risk patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".